Although most of the continuum signal was removed in the preprocessing steps, there are still residuals in the resulting datacubes that will create too many false positives in the detection step, forcing the use of a higher detection threshold and preventing the detection of faint emission line sources. The continuum residuals, as well as the systematics present in the datacube, are subsequently removed with the iterative Principal Component Analysis (PCA) process described in Sect. 3.1.3 of [1]}. The MXDF field of view is segmented into six zones (Fig. REF  left panel; see Sect. 3.1.2 of [1]}). In each segment, a threshold is calculated on the spaxel distribution to evaluate the deviation from the normal distributionThe noise distribution in the MXDF is well represented by a normal distribution, as are the UDF-10 and MOSAIC noise statistics; see Fig. 18 of [3]}.. This threshold is then used by the iterative PCA process to clean the signal from nuisance sources. In the left panel of Fig. REF , we show the number of cleaning iterations at each spaxel. We note that while in most of the spaxels only a few iterations were needed to clean the data, many more were required at specific locations (e.g., at the edge of the field or in the presence of complex bright sources residuals).
